Triple
T18901184
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Ship Who Sang series |
E462343
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object | Helva |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Helva | Statement: [The Ship Who Sang series, featuresCharacter, Helva]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Helva Context triple: [The Ship Who Sang series, featuresCharacter, Helva]
-
A.
Helva
chosen
Helva is a cyborg "brainship" protagonist in Anne McCaffrey's science fiction stories, known for her witty personality and emotional depth despite being encased in a starship.
-
B.
Toffee
Toffee is a calculating, immortal lizard-like monster and master strategist who serves as the primary villain opposing Star Butterfly in the animated series "Star vs. the Forces of Evil."
-
C.
Candy-O
Candy-O is the second studio album by American rock band The Cars, known for its sleek new wave sound and iconic Vargas cover art.
-
D.
Taffy
Taffy is a character featured in the film "On the Line."
-
E.
Toffen
Toffen is a small Swiss municipality in the canton of Bern, located in the Gürbetal valley near the city of Bern.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d8dcfd05bc819088903cca13cc2846 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c52954bc8190a237627c09615ac1 |
completed | April 20, 2026, 6:18 a.m. |
Created at: April 10, 2026, 11:58 a.m.